Modelling of Demand for Tourist Services in Russia

Student: Kazantseva Elena

Educational Programme: Economics and Statistics (Bachelor)

Final Grade: 9

Year of Graduation: 2018

The study is designed to explain the process of forming the demand function for the Russian tourist destination among foreigners. The study considers cross-sectional data of the total number of arrivals from 153 countries to Russia in 2016, depending on twelve economic, political, cultural and social indicators. Cross-sectional modelling is carried out by an OLS, weighted least squares and logarithmic regression methods. A dynamic demand function is provided on the basis of quarterly data from 2010(I) to 2017(III) with logarithmic regression, SARIMA and seasonal Holt-Winters methods used, and on the basis of annual data from 1995 to 2016 with autoregression, logarithmic moving average and non-seasonal Holt-Winters methods used. As a result of the study, the demand functions of inbound tourism in Russia were obtained and used in order to get the international tourist inflows forecast to 2019 in case of quarterly data and to 2025 in case of annual data.

Full text (added May 6, 2018)

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